ThreatDetect is an AI-powered insider threat detection platform that analyzes employee behavioral data and flags individuals who exhibit malicious patterns. It combines an XGBoost classifier with Isolation Forest anomaly detection, then uses SHAP values to explain every prediction in plain language — so your security team understands not just who is flagged, but why. This documentation covers everything you need to install ThreatDetect, prepare your data, run analyses, and interpret results.Documentation Index
Fetch the complete documentation index at: https://mintlify.com/jazbengu/ThreatDetect/llms.txt
Use this file to discover all available pages before exploring further.
Quickstart
Get ThreatDetect running and analyze your first dataset in minutes.
How it works
Understand the detection pipeline: features, model, scoring, and explainability.
CSV batch analysis
Upload an organizational CSV and detect threats across your entire workforce.
Input data schema
Learn exactly which columns your data must contain for accurate predictions.
Key features
- Ensemble detection — XGBoost classifier combined with Isolation Forest anomaly scoring produces robust risk predictions that reduce false positives.
- SHAP explainability — Every prediction, individual or organizational, is accompanied by SHAP-based feature contributions that show which behavioral signals drove the result.
- Three analysis modes — Run a batch scan across your entire organization via CSV upload, analyze a single employee interactively, or explore your dataset visually with the built-in EDA page.
- Downloadable results — Batch analysis produces a results CSV with
Prediction,Risk_Prob,Anomaly_Score, andConfidencecolumns for every employee record. - Global and per-instance explanations — View organization-wide feature importance charts alongside SHAP waterfall plots for individual employees.
ThreatDetect relies on a pre-trained model file located at
AI_Model_Code/insider_threat_model.pkl. This file must be present in the repository root before you launch the app. See the installation guide for details.